Brachial-ankle pulse wave velocity and metabolic syndrome in general population: the APAC study

Similar documents
Relationship between Arterial Stiffness and the Risk of Coronary Artery Disease in Subjects with and without Metabolic Syndrome

Nomogram of the Relation of Brachial-Ankle Pulse Wave Velocity with Blood Pressure

290 Biomed Environ Sci, 2016; 29(4):

Relations of body weight status in early adulthood and weight changes until middle age with metabolic syndrome in the Chinese population

Association between Raised Blood Pressure and Dysglycemia in Hong Kong Chinese

Shihui Fu 1,2, Qixian Wu 3, Leiming Luo 1* and Ping Ye 1*

PULSE WAVE VELOCITY AS A NEW ASSESSMENT TOOL FOR ATHEROSCLEROSIS

Prevalence of diabetes and impaired fasting glucose in Uygur children of Xinjiang, China

Association between multiple comorbidities and self-rated health status in middle-aged and elderly Chinese: the China Kadoorie Biobank study

Arterial Age and Shift Work

Journal of the American College of Cardiology Vol. 48, No. 2, by the American College of Cardiology Foundation ISSN /06/$32.

300 Biomed Environ Sci, 2018; 31(4):

Serum levels of galectin-1, galectin-3, and galectin-9 are associated with large artery atherosclerotic

594 Biomed Environ Sci, 2014; 27(8):

ASSOCIATION OF SYSTEMIC INFLAMMATION WITH ARTERIAL STIFFNESS IN HYPERTENSION

Relationship between cardiovascular risk factors and traditional Chinese constitution in subjects with high-normal blood pressure

ORIGINAL INVESTIGATION. C-Reactive Protein Concentration and Incident Hypertension in Young Adults

Original Article Brachial-ankle pulse wave velocity is associated with carotid intima-media thickness in middle-aged and elderly

Guidelines on cardiovascular risk assessment and management

Cut-Off Value of the Ankle-Brachial Pressure Index at Which the Accuracy of Brachial-Ankle Pulse Wave Velocity Measurement is Diminished

Brachial-ankle pulse wave velocity is an independent predictor of incident hypertension in Japanese normotensive male subjects

Metabolic Syndrome and Workplace Outcome

Biomed Environ Sci, 2016; 29(3): LI Jian Hong, WANG Li Min, LI Yi Chong, ZHANG Mei, and WANG Lin Hong #

Total risk management of Cardiovascular diseases Nobuhiro Yamada

Metabolic Syndrome among Type-2 Diabetic Patients in Benghazi- Libya: A pilot study. Arab Medical University. Benghazi, Libya

Analysis of risk factors of cardiac metabolic abnormality in patients with hypertension.

Zhengtao Liu 1,2,3*, Shuping Que 4*, Lin Zhou 1,2,3 Author affiliation:

Differences in Effects of Age and Blood Pressure on Augmentation Index

Abstract. Introduction

The updated incidences and mortalities of major cancers in China, 2011

Cardiovascular Diseases in CKD

A slightly high-normal glucose level is associated with increased arterial stiffness in Japanese community-dwelling persons with pre-diabetes

Diabetes Care 31: , 2008

Global Coronary Heart Disease Risk Assessment of U.S. Persons With the Metabolic. Syndrome. and Nathan D. Wong, PhD, MPH

Epidemiology of community pre-hypertensive patients and related risk factors in Chengdu city

Prevalence of arterial stiffness in North China, and associations with risk factors of cardiovascular disease: a community-based study

Coronary artery disease (CAD) risk factors

Subdural hemorrhages in acute lymphoblastic leukemia: case report and literature review

The Relationship Between the Acute Changes of the Systolic Blood Pressure and the Brachial-Ankle Pulse Wave Velocity

Letter to the Editor. Association of TCF7L2 and GCG Gene Variants with Insulin Secretion, Insulin Resistance, and Obesity in New-onset Diabetes *

Arterial stiffness index: A new evaluation for arterial stiffness in elderly patients with essential hypertension

Pulse wave velocity, augmentation index and arterial age in students

Socioeconomic status risk factors for cardiovascular diseases by sex in Korean adults

Association between arterial stiffness and cardiovascular risk factors in a pediatric population

Vascular Compliance is Reduced in Geriatric People with Angiographic Coronary Atherosclerosis

Central pressures and prediction of cardiovascular events in erectile dysfunction patients

A CORRELATIVE STUDY SHOWING THE RELATIONSHIP OF SALIVARY URIC ACID LEVEL WITH THE METABOLIC SYNDROME COMPONENTS & ITS SEVERITY

ALT and aspartate aminotransferase (AST) levels were measured using the α-ketoglutarate reaction (Roche,

Rehabilitation and Research Training Center on Secondary Conditions in Individuals with SCI. James S. Krause, PhD

Figure S1. Comparison of fasting plasma lipoprotein levels between males (n=108) and females (n=130). Box plots represent the quartiles distribution

The Brachial Ankle Pulse Wave Velocity is Associated with the Presence of Significant Coronary Artery Disease but Not the Extent

MDCT による冠動脈狭窄や石灰化スコアの評価と PWV の関連性

ORIGINAL ARTICLE. Abstract. Introduction

Theoretical and practical questions in the evaluation of arterial function Miklós Illyés MD. Ph.D.

The Diabetes Epidemic in Korea

Hypertriglyceridemia and the Related Factors in Middle-aged Adults in Taiwan

Amlodipine/atorvastatin has an effect on vascular function and normal lipid levels.

Original Research Article

Association of hypothyroidism with metabolic syndrome - A case- control study

Clinical Features and Subtypes of Ischemic Stroke Associated with Peripheral Arterial Disease

programme. The DE-PLAN follow up.

Cross-section analysis of coal workers pneumoconiosis and higher brachial-ankle pulse wave velocity within Kailuan study

The investigation of serum lipids and prevalence of dyslipidemia in urban adult population of Warangal district, Andhra Pradesh, India

Comparison of Abnormal Cholesterol in Children, Adolescent & Adults in the United States, : Review

Impact of Physical Activity on Metabolic Change in Type 2 Diabetes Mellitus Patients

Metabolic syndrome in Korean adolescents and young adult offspring and their parents

pulmonary artery vasoreactivity in patients with idiopathic pulmonary arterial hypertension

Internal and Emergency Medicine Official Journal of the Italian Society of Internal Medicine. ISSN Volume 8 Number 3

Diabetes Care Publish Ahead of Print, published online August 19, 2010

ARTERIAL STIFFNESS AND CORONARY ARTERY DISEASE

Prevalence of and Risk Factors for Type 2 Diabetes Mellitus in Hyperlipidemia in China

The Impact Of Adiposity And Insulin Resistance On Endothelial Function In Middle-Aged Subjects

Comparison of the Assessment of Orthostatic Hypotension Using Peripheral and Central Blood Pressure Measurements

SCIENTIFIC STUDY REPORT

Impact of Body Mass Index and Metabolic Syndrome on the Characteristics of Coronary Plaques Using Computed Tomography Angiography

Relationship of Waist Circumference and Lipid Profile in Children

Risk Factors for Heart Disease

Diabetology & Metabolic Syndrome. Open Access RESEARCH

Predictive value of overweight in early detection of metabolic syndrome in schoolchildren

ARIC Manuscript Proposal # PC Reviewed: 2/10/09 Status: A Priority: 2 SC Reviewed: Status: Priority:

Relationship of Body Mass Index, Waist Circumference and Cardiovascular Risk Factors in Chinese Adult 1

ORIGINAL ARTICLE AMBULATORY BLOOD PRESSURE IN OBESITY. Introduction. Patients and Methods

CARDIOVASCULAR RISK FACTORS & TARGET ORGAN DAMAGE IN GREEK HYPERTENSIVES

Shihui Fu 1,2, Ying Lin 2, Leiming Luo 1* and Ping Ye 1*

Table S1. Characteristics associated with frequency of nut consumption (full entire sample; Nn=4,416).

Title: Associations of sitting time and occupation with metabolic syndrome in South Korean adults: a cross-sectional study

Supplementary Appendix

Background. Metabolic syndrome T2DM CARDIOVASCULAR DISEASE. Major Unmet Clinical Need. Novel Risk Factors. Classical Risk Factors LDL-C.

An evaluation of body mass index, waist-hip ratio and waist circumference as a predictor of hypertension across urban population of Bangladesh.

Different worlds, different tasks for health promotion: comparisons of health risk profiles in Chinese and Finnish rural people

Metabolic Syndrome: What s in a name?

Metabolic Disorders Increase the Risk to Incident Cardiovascular Disease in Middle aged and Elderly Chinese *

Relationship between Biological Markers, Metabolic Components, Lifestyles, and Impaired Fasting Glucose in Male Workers

Biomarkers and undiagnosed disease

The incidence of cardiovascular disease (CVD), one

Metabolic Syndrome: Why Should We Look For It?

Submitted 15 July 2011: Accepted 13 December 2011: First published online 10 February 2012

Biomed Environ Sci, 2014; 27(8):

Gender-specific association between pulse pressure and C-reactive protein in a Chinese population

Transcription:

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 DOI 10.1186/s12872-016-0409-x RESEARCH ARTICLE Open Access Brachial-ankle pulse wave velocity and metabolic syndrome in general population: the APAC study Anxin Wang 1,2,3,4,5, Zhaoping Su 6, Xiaoxue Liu 7, Yuling Yang 8, Shuohua Chen 9, Suzhen Wang 6, Yanxia Luo 5, Xiuhua Guo 5*, Xingquan Zhao 1,2,3,4* and Shouling Wu 9* Abstract Background: Metabolic syndrome (MetS) is correlated with arterial stiffness and can be evaluated by brachialankle pulse wave velocity (bapwv). We investigated potential associations between MetS and bapwv in a Chinese community population. Methods: The community-based Asymptomatic Polyvascular Abnormalities in Community study examined asymptomatic polyvascular abnormalities in a Chinese population aged 40 years. The relationship between MetS and its components and bapwv was analyzed by multivariate logistic and linear regression models. Results: Out of 5181 study participants, 1271 subjects (24.53%) had MetS. Mean values of bapwv in subjects with 0, 1, 2,3, 4, and 5 components of MetS were 1430, 1526, 1647, 1676,1740, and 1860 cm/s, respectively (p < 0.001 for trend). After adjusting for confounding risk factors, MetS was significantly associated with bapwv (odds ratio [OR]: 2.74; 95% CI: 2.28, 3.30). Among the five components of MetS, elevated blood pressure was the most important factor for bapwv. All models of multivariate linear regression analysis showed a significant positive correlation between the increasing numbers of MetS components and bapwv (p < 0.0001). Conclusions: bapwv was associated with MetS and was greater with increasing numbers of MetS components. Elevated blood pressure was the most important factor for bapwv. Keywords: Brachial-ankle pulse wave velocity, Metabolic syndrome, Arterial stiffnes, Cardio-cerebrovascular diseases Background Metabolic syndrome (MetS) is a pre-atherosclerotic state which involves a cluster of factors, such as abdominal obesity, arterial hypertension, dyslipidemia, and hyperglycemia, and is closely associated with a marked increase in the risk of cardio-cerebrovascular diseases and type 2 * Correspondence: statguo@ccmu.edu.cn; zxq@vip.163.com; drwusl@163.com Equal contributors 5 Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, People s Republic of China 1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 6 Tiantanxili, Dongcheng District, Beijing 100050, People s Republic of China 9 Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No. 57 Xinhua Road, Lubei District, Tangshan 063000, People s Republic of China Full list of author information is available at the end of the article diabetes mellitus [1 3]. Some studies have shown that MetS is correlated with arterial stiffness. Nakanishi et al. suggested that persistent MetS conditions can deteriorate the severity of arterial stiffness [4, 5]. Furthermore, Tomiyama et al. suggested that an improvement in MetS status could delay the progression of atherosclerosis [6]. Pulse wave velocity is an objective valid index of arterial stiffness and is widely used for non-invasive evaluation of subclinical atherosclerotic changes [7]. Brachial-ankle pulse wave velocity (bapwv), a type of pulse wave velocity, is a promising test method that can assess the stiffness of both aortic and peripheral arteries [8, 9]. bapwv not only reflects early atherosclerotic change [10 12], but also serves as a valuable predictor of mortality due to cardio-cerebrovascular events [13]. In the past decade, studies have investigated the relationship between arterial The Author(s). 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 2 of 10 stiffness measured by bapwv and the components of MetS in different populations worldwide. However, the association of bapwv with MetS is not understood well. The correlation between bapwv and MetS and its components may be different based on different populations, regions and cultural diet. The purpose of the present study was to evaluate the relationship between bapwv and MetS and its individual components in a large sample size of 5181 communitybased subjects in the northern region of China, and to further elucidate the complex correlation between bapwv and MetS. Methods Study population The Asymptomatic Polyvascular Abnormalities Community (APAC) study is a community-based observational prospective, long-term follow-up study to investigate the epidemiology of asymptomatic polyvascular abnormalities in Chinese adults [14]. The study cohort was a subgroup of a previously described population of the Kailuan study [15]. Data about patient demographics, clinical characteristics (physical examination, laboratory tests, carotid duplex ultrasound and transcranial Doppler examinations), and also finished structured interviews with a standardized questionnaire performed by trained investigators. Anthropometric indices included height and weight. Body mass index (BMI) was calculated as body weight (kg) divided by the square of body height (m 2 ). Blood pressure was measured twice with an appropriate cuff size in relation to arm size, in the participants with the supine position after 10 min resting. The average of the two readings was used. However, if the difference between the two measurements exceeded 5 mmhg, a third reading would be conducted, and the average of three readings was recorded and analyzed. Smoking was defined as at least one cigarette per day for more than a year. Alcohol abuse was defined as alcohol intake of at least 90 and 45 g of liquor a day for men and women, respectively, for more than 1 year. Smoking or drinking cessation was considered only if it lasted for at least 1 year. Details of the APAC study design and the information on baseline characteristics have been published previously. The community is part of a large coal mining industry in Tangshan, Hebei Province [15, 16], China. The study protocol was approved by the Ethics Committees of the Kailuan General Hospital and the Beijing Tiantan Hospital, and informed consent was obtained from all participants. Definition of MetS MetS was defined using previously published criteria from the International Diabetes Federation [11]. The definition included the presence of central obesity (waist circumference >90 cm for Chinese men and >80 cm for Chinese women), plus any two of the following factors: triglycerides >150 mg/dl (1.7 mmol/l) or obtaining therapy for increased triglyceride (TG) concentrations; highdensity lipoprotein cholesterol (HDL-C), 40 mg/dl (1.03 mmol/l) in men and 50 mg/dl (1.29 mmol/l) in women, or obtaining therapy for low HDL-C level; systolic blood pressure (BP) >130 mmhg or diastolic BP >85 mmhg, or treatment of previously diagnosed arterial hypertension; fasting plasma glucose >100 mg/dl (5.6 mmol/l) or previously diagnosed type 2 diabetes mellitus. Measurement of bapwv Bilateral bapwv was evaluated by utilizing abp-203rpe III device ( Omron Healthcare, Kyoto, Japan). Details about this instrument and its use have been described, and clinical validation and good reproducibility have been confirmed [8]. All examinations were carried out by specially trained physicians and nurses. All subjects were light clothing and underwent examination under resting-state by placement of the subject in a supine position without a pillow. Electrodes of the electrocardiograph were located in both wrists, a stethoscope was located in the left border of the sternum for acquiring heart sounds, and cuffs were wrapped with certain strain on both the upper arms and ankles. The lower border of the brachial cuff was located 2 3 cm above the chelidon, and the lower border of ankle cuff was located 1 2 cm above the medial malleolus. Two measured values were recorded from both sides of the body, while the second value of bapwv was utilized. Then we used the higher of the left and right bapwv values for analyses [17]. Arterial stiffness was considered as bapwv 1400 cm/s, since this is what has been identified as an independent risk factor in the Framingham score and can distinguish patients with atherosclerotic cardiovascular disease. Diabetes was considered as fasting plasma glucose concentration of 7.0 mmol/l or treatment for diabetes with drug or insulin. Hypertension was defined as systolic BP >130 mmhg or diastolic BP >85 mmhg or on drug treatment for hypertension. Statistical analysis The continuous variables and categorical data are expressed as the mean ± standard deviation (SD) and percentage, respectively. The Student s t-test or ANOVA test was used to address non-paired samples for the comparison of normally distributed parameters, and the Wilcoxon or Kruskal-Wallis test for the comparison of non-parametric variables. The qualitative variables were compared by using chi-squared test. Four multivariate logistic regression analyses were performed to calculate odds ratio (OR) and 95% confidence interval (CI) for the associations of MetS or the number of MetS components (the 0 MetS component

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 3 of 10 group was used as the reference category). Arterial stiffness was defined as bapwv 1400 cm/s. Model 1 was the crude model; Model 2 adjusted for age and gender; Model 3 adjusted for age, gender, level of education, income, smoking, alcohol abuse, and physical activity; and Model 4 adjusted for age, gender, level of education, income, smoking, alcohol abuse, amount of physical activity, BMI, and serum concentrations of low-density lipoprotein cholesterol (LDL-C) and high-sensitivity C-reactive protein. Finally, for each model, a trend test was performed after the number of MetS components as a continuous variable entering into the model. Furthermore, a multivariate linear regression was applied to analyze the independent associations between bapwv and MetS. Differences were considered statistically significant only when p-value was <0.05. All data were analyzed with a commercially available software Table 1 Clinical and biochemical characteristics of subjects with and without metabolic syndrome Variables Total (n = 5181) MetS group (n = 1271) Non-MetS group (n = 3910) P value Age (year) 55.16 ± 11.80 56.29 ± 10.47 54.79 ± 12.18 <0.0001 Male, n (%) 3108 (59.99) 701 (55.15) 2407 (61.56) <0.0001 Education, n (%) Illiteracy/Primary School 638 (12.31) 188 (14.79) 450 (11.51) 0.0004 Middle School 2295 (44.30) 583 (45.87) 1712 (43.79) High School or Higher 2248 (43.39) 500 (39.34) 1748 (44.71) Income, n (%) < 1000 1239 (23.91) 264 (20.77) 975 (24.94) 0.0001 1000 3000 3431 (66.22) 903 (71.05) 2528 (64.65) > 3000 511 (9.86) 104 (8.18) 407 (10.41) Body Mass Index (kg/m2) 24.94 ± 3.25 27.38 ± 3.00 24.15 ± 2.92 <0.0001 Waist circumference (cm) 86.12 ± 9.66 93.90 ± 7.26 83.59 ± 8.96 <0.0001 Waist-to hip ratio 0.88 ± 0.06 0.91 ± 0.06 0.87 ± 0.06 <0.0001 Systolic Blood Pressure (mmhg) 131.33 ± 20.04 141.18 ± 18.36 128.12 ± 19.51 <0.0001 Diastolic Blood Pressure (mmhg) 82.86 ± 11.06 88.10 ± 10.79 81.16 ± 10.60 <0.0001 Fasting Plasma Glucose (mmol/l) 5.59 ± 1.51 6.37 ± 2.01 5.33 ± 1.20 <0.0001 Total cholesterol (mmol/l) 1.53 ± 0.70 1.69 ± 0.74 1.48 ± 0.68 <0.0001 Triglycerides (mmol/l) 1.68 ± 1.42 2.60 ± 2.01 0.38 ± 1.00 <0.0001 High-Density Lipoprotein-Cholesterol ( mmol/l) 1.63 ± 0.46 1.45 ± 0.41 1.68 ± 0.46 <0.0001 Low-Density Lipoprotein-Cholesterol (mmol/l) 2.63 ± 0.74 2.76 ± 0.87 2.58 ± 0.69 <0.0001 High-Sensitivity C-Reactive Protein 2.13 ± 4.18 2.77 ± 4.25 1.92 ± 4.14 <0.0001 bapwv (cm/s) 1588.40 ± 401.62 1703.30 ± 371.57 1551.06 ± 403.98 <0.0001 Hypertension, n (%) 2500 (48.25) 980 (77.10) 1520 (38.87) <0.0001 Diabetes mellitus, n (%) 629 (12.14) 348 (27.38) 281 (7.19) <0.0001 Smoking, n (%) Never 3233 (62.40) 812 (63.89) 2421 (61.92) 0.3655 Former 291 (5.62) 73 (5.74) 218 (5.58) Current 1657 (31.98) 386 (30.37) 1271 (32.51) Alcohol abuse, n (%) Never 3391 (65.51) 833 (65.54) 2561 (65.50) 0.7074 Former 81 (1.56) 23 (1.81) 58 (1.48) Current 1706 (32.93) 415 (32.65) 1291 (33.02) Physical Activity, n (%) Inactive 2087 (40.28) 506 (39.81) 1581 (40.43) 0.6289 Moderately Active 1312 (25.32) 314 (24.70) 998 (25.52) Very Active 1782 (34.39) 451 (35.48) 1331 (34.04) MetS metabolic syndrome, bapwv brachial-ankle pulse wave velocity

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 4 of 10 program (SAS software version 9.3; SAS Institute Inc., Cary, NC, USA). Results Of the 5440 subjects who were originally included into the APAC study, we excluded 218 participants without measurement of bapwv and 41 individuals without MetS. Eventually, 5181 participants (3108 men, 2073 women) with a mean age of 55.16 ± 11.80 years (range: 40 94 years) were included in the present investigation. The distribution of demographics, anthropometric measurement, bapwv, vascular risk factors and living habits according to presence of metabolic syndrome are summarized in Table 1. At baseline, 1271 out of 5181 subjects (24.53%) had MetS. Compared with those with no MetS, the incidence of MetS was found significantly in older subjects, in higher proportion of men, in subjects with lower level of education, subjects at the middleincome level (p < 0.001 for all). There were no statistically significant differences for smoking (p = 0.3655), drinking (p = 0.7074) and physical activity (p = 0.6289) between the MetS group and the group without MetS. The bapwv values were significantly and positively correlated with the values of the components of MetS (p < 0.0001). Mean values of bapwv in subjects with 0, 1, 2,3, 4, and 5 features of MetS were 1430, 1526, 1647, 1676,1740, and 1860 cm/s, respectively (p < 0.001 for trend) (Fig. 1). The characteristics of the participants in relation to bapwv are shown in Table 2. There were significant differences between the two groups in mean age and sex (p < 0.0001 for both). The percentage of MetS and its components was higher in the arterial stiffness group (bapwv 1400 cm/s) than the non-arterial stiffness group (bapwv <1400 cm/s), and a higher proportion of subjects in the arterial stiffness group than those in the non-arterial stiffness group had exceeded thresholds for BMI, waist circumference, waist-to-hip ratio, systolic BP, diastolic BP, fasting plasma glucose, total cholesterol, triglycerides, HDL-C, LDL-C, and high-sensitivity C- reactive protein (p < 0.0001 for all). There was a trend toward higher age, education, hypertension, diabetes mellitus, smoking, alcohol abuse, and less or no physical activity in the arterial stiffness group than in the nonarterial stiffness group (p < 0.0001 for all). The severity of central obesity, elevated arterial BP, raised fasting plasma glucose and TG, and reduced HDL-C concentration and the degree of MetS were significantly higher in the arterial stiffness group than in the group without arterial stiffness. In all four models of the multivariable logistic regression analysis, the risk of arterial stiffness increased significantly (p < 0.0001) with increasing number of MetS components (Table 3). After adjustment for age, gender, level of education, income, smoking, alcohol abuse, amount of physical activity, BMI, and serum concentrations of LDL-C, high-sensitivity C-reactive protein (Model 4), MetS remained significantly associated with Fig. 1 Mean bapwv according to the number (0, 1, 2, 3, 4, 5) of components of metabolic syndrome. MetS: metabolic syndrome; bapwv: brachial ankle pulse wave velocity

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 5 of 10 Table 2 Clinical and biochemical characteristics of bapwv Variables bapwv < 1400cm/s (n = 1965) bapwv 1400cm/s (n = 3216) P value Age (year) 48.14 ± 6.39 59.45 ± 12.28 <0.0001 Male, n 944 (48.04) 2164 (67.29) <0.0001 Education, n (%) Illiteracy/Primary School 97 (4.94) 541 (16.82) <0.0001 Middle School 856 (43.56) 1439 (44.75) High School or Higher 1012 (51.50) 1236 (38.43) Income, n (%) < 1000 530 (26.97) 709 (22.05) <0.0001 1000 3000 1278 (65.04) 2153 (66.95) > 3000 157 (7.99) 354 (11.01) Body Mass Index (kg/m2) 24.05 ± 3.09 25.12 ± 3.34 <0.0001 Waist circumference (cm) 83.36 ± 9.55 87.80 ± 9.33 <0.0001 Waist-to hip ratio 0.86 ± 0.06 0.89 ± 0.06 <0.0001 Systolic Blood Pressure (mmhg) 118.78 ± 14.16 138.99 ± 19.22 <0.0001 Diastolic Blood Pressure (mmhg) 79.11 ± 9.62 85.15 ± 11.25 <0.0001 Fasting Plasma Glucose (mmol/l) 5.24 ± 0.96 5.80 ± 1.73 <0.0001 Total cholesterol (mmol/l) 1.42 ± 0.64 1.60 ± 0.73 <0.0001 Triglycerides (mmol/l) 1.50 ± 1.25 1.78 ± 1.50 <0.0001 High-Density Lipoprotein-Cholesterol (mmol/l) 1.67 ± 0.47 1.60 ± 0.44 <0.0001 Low-Density Lipoprotein-Cholesterol (mmol/l) 2.54 ± 0.66 2.68 ± 0.78 <0.0001 High-Sensitivity C-Reactive Protein 1.51 ± 2.83 2.51 ± 4.79 <0.0001 Hypertension, n (%) 427 (21.73) 2073 (64.46) <0.0001 Diabetes mellitus, n (%) 94 (4.78) 535 (16.64) <0.0001 Smoking, n (%) Never 1334 (67.89) 1899 (59.05) <0.0001 Former 59 (3.00) 232 (7.21) Current 572 (29.11) 1085 (33.74) Alcohol abuse, n (%) Never 1401 (71.30) 1993 (61.97) <0.0001 Former 18 (0.92) 63 (1.96) Current 546 (27.79) 1160 (36.07) Physical Activity, n (%) Inactive 877 (44.63) 1210 (37.62) <0.0001 Moderately Active 561 (28.55) 751 (23.35) Very Active 527 (26.82) 1255 (39.02) Metabolic Syndrome, n (%) 261 (13.28) 1010 (31.41) <0.0001 Metabolic Syndrome Components Central Obesity, n (%) 907 (46.16) 1838 (57.15) <0.0001 Raised Triglycerides, n (%) 523 (26.62) 1152 (35.82) <0.0001 Reduced High-Density Lipoprotein-Cholesterol, n (%) 169 (8.60) 419 (13.03) <0.0001 Raised Blood Pressure, n (%) 378 (19.24) 1820 (56.59) <0.0001 Raised Fasting Plasma Glucose, n (%) 455 (23.16) 1267 (39.40) <0.0001 Metabolic Syndrome (No. of Components) 0, n (%) 608 (30.94) 394 (12.25) <0.0001

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 6 of 10 Table 2 Clinical and biochemical characteristics of bapwv (Continued) 1, n (%) 644 (32.77) 751 (23.35) 2, n (%) 427 (21.73) 959 (29.82) 3, n (%) 216 (10.99) 681 (21.18) 4, n (%) 64 (3.26) 371 (11.54) 5, n (%) 6 (0.31) 60 (1.87) bapwv brachial ankle pulse wave velocity bapwv (OR: 2.74; 95% CI: 2.28 3.30). Among the five components of MetS, raised BP was the most important factor for bapwv. The OR values were 4.60 for raised BP, 1.50 for raised fasting plasma glucose, 1.48 for reduced HDL-C, 1.38 for raised triglycerides, and 1.18 for central obesity. Using the subgroup with no component of MetS as baseline, the ORs for the associations between the subgroups with 1, 2, 3, 4 and 5 MetS components and bapwv were 1.97 (95% CI: 1.60, 2.43), 3.80 (95% CI: 3.04, 4.75), 5.70 (95% CI: 4.38, 7.42), 11.66 (95% CI: 8.16, 16.67), and 20.88 (95% CI: 8.37, 52.04), respectively. In this multivariate model, the bapwv increased significantly (p < 0.0001 for trend) with the number of MetS components. The same held true for the three other models of the multivariate analysis (Table 3). Figure 2 shows the results of multiple logistic regression analysis of the association between MetS components and bapwv in males and females (Model 4). In this model, metabolic syndrome and its components were associated with increased bapwv in both males and females. Among the five components of MetS, raised BP was still the most important factor for bapwv. Furthermore, regardless of gender, all models of the multivariate linear regression analysis in Table 4 showed a significant positive correlation between bapwv and MetS (p < 0.0001). Discussion In our investigation based on a community population in northern China, bapwv was significantly associated with MetS and bapwv, and there was greater statistical significance with increasing numbers of MetS components. Among the conditions of central obesity, raised triglycerides, reduced HDL-C, raised BP, and raised fasting plasma glucose; raised BP was the strongest determinant for bapwv. Furthermore, the mean velocity of bapwv in subjects with five components of MetS had a 1.3 times faster than individuals with no MetS. Table 3 Odds ratio and 95% CI of bapwv for MetS/components in multiple logistic regression analysis Variables Model 1 Model 2 Model 3 Model 4 Metabolic Syndrome 2.99 (2.57 3.47) 2.99 (2.54 3.53) 2.93 (2.48 3.46) 2.74 (2.28 3.30) Central Obesity 1.10 (0.97 1.25) 1.11 (0.96 1.29) 1.08 (0.93 1.26) 1.18 (0.98 1.42) Raised Triglycerides 1.12 (0.98 1.29) 1.36 (1.16 1.59) 1.36 (1.17 1.60) 1.38 (1.17 1.62) Reduced High-Density Lipoprotein Cholesterol 1.46 (1.19 1.79) 1.39 (1.10 1.76) 1.40 (1.10 1.78) 1.48 (1.17 1.89) Raised Blood Pressure 4.99 (4.36 5.71) 4.51 (3.88 5.25) 4.44 (3.82 5.18) 4.60 (3.93 5.39) Raised Fasting Plasma Glucose 1.76 (1.54 2.01) 1.60 (1.38 1.14) 1.58 (1.35 1.84) 1.50 (1.28 1.76) No. of Components 0 Reference Reference Reference Reference 1 1.80 (1.53 2.12) 1.89 (1.55 2.31) 1.87 (1.53 2.29) 1.97 (1.60 2.43) 2 3.47 (2.92 4.11) 3.51 (2.86 4.30) 3.38 (2.76 4.15) 3.80 (3.04 4.75) 3 4.86 (3.99 5.94) 4.98 (3.96 6.27) 4.80 (3.81 6.05) 5.70 (4.38 7.42) 4 8.94 (6.67 12.00) 9.82 (7.11 13.56) 9.39 (6.79 12.98) 11.66 (8.16 16.67) 5 15.43 (6.60 36.06) 15.80 (6.51 38.32) 15.35 (6.30 37.38) 20.88 (8.37 52.04) P for trend <0.0001 <0.0001 <0.0001 <0.0001 MetS metabolic syndrome, bapwv brachial ankle pulse wave velocity Model 1: unadjusted Model 2: adjusted for age and gender Model 3: adjusted for age, gender, level of education, income, smoking, alcohol abuse, and amount of physical activity Model 4: adjusted for age, gender, level of education, income, smoking, alcohol abuse, amount of physical activity, body mass index, and serum concentrations of low-density lipoprotein cholesterol, high-sensitivity C-reactive protein

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 7 of 10 Fig. 2 Odds ratio and 95% CI of bapwv for MetS/its Components in Multiple Logistic Regression Analysis in different gradation of gender after adjusted. MetS: metabolic syndrome; bapwv: brachial ankle pulse wave velocity; TG: triglyceride; HDL-C: high-density lipoprotein cholesterol; BP: blood pressure; FPG: fasting plasma glucose Table 4 Multivariate linear regression analysis models of associations between number of MetS components and the level of bapwv Variables MetS Increasing 1 component of MetS B (95%CI) P Value B (95%CI) P Value Model 1 152.24 (127.16 177.32) <0.0001 81.21 (72.82 89.60) <0.0001 Model 2 125.39 (106.03 144.75) <0.0001 64.40 (57.92 70.88) <0.0001 Model 3 122.17 (102.80 141.53) <0.0001 63.07 (56.57 69.58) <0.0001 Model 4 132.74 (111.13 154.35) <0.0001 77.71 (70.12 85.31) <0.0001 Female Model 1 267.94 (235.39 300.50) <0.0001 118.25 (107.83 128.66) <0.0001 Model 2 129.63 (104.40 154.86) <0.0001 59.27 (50.69 67.85) <0.0001 Model 3 125.63 (100.30 150.95) <0.0001 58.03 (49.38 66.68) <0.0001 Model 4 127.85 (100.20 155.50) <0.0001 66.78 (56.80 76.76) <0.0001 Male Model 1 82.90 (47.96 117.83) <0.0001 52.95 (41.01 64.89) <0.0001 Model 2 107.28 (79.16 135.40) <0.0001 63.80 (54.27 73.32) <0.0001 Model 3 105.18 (77.09 133.26) <0.0001 62.51 (52.97 72.05) <0.0001 Model 4 126.18 (94.48 157.89) <0.0001 81.93 (70.80 93.06) <0.0001 MetS metabolic syndrome, bapwv brachial ankle pulse wave velocity Model 1: unadjusted Model 2: adjusted for age and gender Model 3: adjusted for age, gender, level of education, income, smoking, alcohol abuse, and amount of physical activity Model 4: adjusted for age, gender, level of education, income, smoking, alcohol abuse, amount of physical activity, body mass index, and serum concentrations of low-density lipoprotein cholesterol, high-sensitivity C-reactive protein

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 8 of 10 Our findings demonstrate that components of MetS for the influence of vasculature appear to be additive. This result was consistent with those of other studies [5, 10, 18]. The individuals with more risk factors have substantially greater bapwv values than those with fewer risk factors, which can be explained by bapwv being closely associated with severity of arterial stiffness. In a Japanese population study, Nakanishi et al. [5] showed that age-adjusted mean values of bapwv were increased with clustered features of MetS in both sexes. In addition, insulin resistance was closely associated with the risk for increased bapwv or increased arterial stiffness. However, in our study, raised BP was the strongest determinant for risk of increased bapwv. However, the mechanism by which MetS might increase bapwv remains unclear. One probable explanation for our findings is that elevated BP can increase bapwv by directly acting on the arterial wall. Angelo Scuteri et al. [11] conducted a study involving nine cohorts representing eight different European countries and the United States and suggested that the risky cluster of raised triglycerides, raised BP, central obesity, raised fasting plasma glucose, and central obesity was significantly associated with extremely stiff arteries. They also showed the highest prevalence in Sardinian, Italian, British, and Belgian cohorts, and the lowest in cohorts from Sweden and the United States. However, Young-Kwon Kim [18] found that the other individual MetS components, except for a raised BP, do not affect arterial stiffness independently. Another study [19] including 8599 subjects in south China suggested that bapwv was significantly higher in subjects with MetS than in those without MetS (p <0.001 for both sexes). All the metabolic components were correlated to bapwv in the male and female subjects except low HDL-C and high urine acid in the male group. BP and fasting plasma glucose had the strongest correlation factors. The bapwv values were positively correlated with advanced age (p < 0.001) and the values of the MetS components, and this correlation was stronger in females than in males (p < 0.001), which is different from the results summarized by Wang et al. [20]. Although the current study focused on the feasibility of a non-invasive bapwv examination as an effective tool to screen community populations at high risk of MetS, appropriate cut-off points or valid intervals of bapwv were not achieved [20 23]. With the marked growth of living standards in China, prevalence of MetS has increased and has resulted in serious social burden [24, 25]. Arterial stiffness is an indicator of arterial damage and its increase with age has been demonstrated to be associated with an increased risk of cardio-cerebrovascular diseases [26 29]. The clinical implication of our study is that community populations with bapwv >1400 cm/ s, advanced age, and MetS with reduced HDL-C, raised BP and raised fasting plasma glucose, might benefit from immediate intervention strategies which reduce the risk of further cardiovascular disease morbidity and mortality [30]. There are some potential limitations in our study. First, our community-based investigation, which is a cross-sectional investigation, cannot prove a causal relationship, since this has to be demonstrated in a longitudinal study. The data from this study only allows us to summarize the relationships between bapwv and MetS components, while the influence of MetS as a risk factor for cardio-cerebrovascular diseases may be shown in follow-up studies. Second, this study was based on the participants of the large Kailuan Study which included employees, retirees and their families of the Kailuan Company. Although we used a rigid random sampling method to reduce selection bias, the population of the Kailuan Company does not necessarily represent the populations of Hebei province. Finally, a crucial topic is the alteration of the results of the bapwv measurements by BP levels themselves. Conclusions In conclusion, our study is based on more than 5000 subjects, showing that increasing the number of MetS components is significantly correlated with a risk for increased bapwv in a northern China communitybased population. A decrease in arterial compliance or an increase in arterial stiffness was shown to be related to a risk for cardiovascular mortality, for this reason, individuals with clustered components of MetS might benefit from immediate interventions, including frequent exercise, reasonable diet regulation, and medical therapy for MetS. Furthermore, bapwv may be taken into consideration as a screening index in community-based healthcare plans and as a tool for evaluating the risk of cardiocerebrovascular diseases in clinical practice. Abbreviations APAC: Asymptomatic polyvascular abnormalities community; bapwv: brachial-ankle pulse wave velocity; BMI: Body mass index; BP: Blood pressure; CI: Confidence internals; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; MetS: Metabolic syndrome; OR: Odds ratio; SD: Standard deviation; TG: Triglyceride Acknowledgements We thank all participating hospitals, colleagues, nurses, and imaging and laboratory technicians, as well as to the project development and management teams in Beijing Tiantan hospital and the Kailuan Group. Funding This study was supported by the Program of National Natural Science Foundation of China (Serial Number: 81530087 and 81473071), Natural Science Foundation of Shandong Province (ZR2013HM045) and the National Bureau of Statistics of China (2013LY013).

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 9 of 10 Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Authors contributions XZ and SW planned and designed the study. XL, YY, SC, SW, YL, XG contributed to the acquisition and interpretation of data. AW and ZS analyzed the data. AW and ZS were primarily responsible for writing the paper. XG, SW and XZ revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Competing interests The authors declare that they have no competing interests. Consent for publication Not applicable. Ethics approval and consent to participate The study was approved by the Ethics Committees of both Kailuan General Hospital and Beijing Tiantan Hospital, and was in compliance with the Declaration of Helsinki. Written informed consent was obtained from all participants. Author details 1 Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 6 Tiantanxili, Dongcheng District, Beijing 100050, People s Republic of China. 2 China National Clinical Research Center for Neurological Diseases, Beijing, People s Republic of China. 3 Center of Stroke, Beijing Institute for Brain Disorders, Beijing, People s Republic of China. 4 Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, People s Republic of China. 5 Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, People s Republic of China. 6 Department of Epidemiology and Health Statistics, Academy of public health and management, Weifang Medical University, No. 7166 Baotongxijie, Weicheng District, Weifang 261053, People s Republic of China. 7 Department of Cardiology, Tangshan People s Hospital, Tangshan, People s Republic of China. 8 Graduate School, North China University of Science and Technology, Tangshan, People s Republic of China. 9 Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No. 57 Xinhua Road, Lubei District, Tangshan 063000, People s Republic of China. Received: 11 March 2016 Accepted: 14 November 2016 References 1. Zhou F, Zhang H, Yao W, Mei H, Xu D, Sheng Y, Yang R, Kong X, Wang L, Zou J, et al. Relationship between brachial-ankle pulse wave velocity and metabolic syndrome components in a Chinese population. J Biomed Res. 2014;28(4):262 8. 2. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith Jr SC. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640 5. 3. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 2006;23(5):469 80. 4. Nakanishi N, Suzuki K, Tatara K. Clustered features of the metabolic syndrome and the risk for increased aortic pulse wave velocity in middleaged Japanese men. Angiology. 2003;54(5):551 9. 5. Nakanishi N, Shiraishi T, Wada M. Brachial-ankle pulse wave velocity and metabolic syndrome in a Japanese population: the Minoh study. Hypertens Res. 2005;28(2):125 31. 6. Tomiyama H, Hirayama Y, Hashimoto H, Yambe M, Yamada J, Koji Y, Motobe K, Shiina K, Yamamoto Y, Yamashinai A. The effects of changes in the metabolic syndrome detection status on arterial stiffening: a prospective study. Hypertens Res. 2006;29(9):673 8. 7. Sipila K, Koivistoinen T, Moilanen L, Nieminen T, Reunanen A, Jula A, Salomaa V, Kaaja R, Koobi T, Kukkonen-Harjula K, et al. Metabolic syndrome and arterial stiffness: the Health 2000 Survey. Metabolism. 2007;56(3):320 6. 8. Yamashina A, Tomiyama H, Takeda K, Tsuda H, Arai T, Hirose K, Koji Y, Hori S, Yamamoto Y. Validity, reproducibility, and clinical significance of noninvasive brachial-ankle pulse wave velocity measurement. Hypertens Res. 2002;25(3):359 64. 9. Tomiyama H, Yamashina A, Arai T, Hirose K, Koji Y, Chikamori T, Hori S, Yamamoto Y, Doba N, Hinohara S. Influences of age and gender on results of noninvasive brachial-ankle pulse wave velocity measurement a survey of 12517 subjects. Atherosclerosis. 2003;166(2):303 9. 10. Weng C, Yuan H, Tang X, Huang Z, Yang K, Chen W, Yang P, Chen Z, Chen F. Age- and gender dependent association between components of metabolic syndrome and subclinical arterial stiffness in a Chinese population. Int J Med Sci. 2012;9(8):730 7. 11. Scuteri A, Cunha PG, Rosei EA, Badariere J, Bekaert S, Cockcroft JR, Cotter J, Cucca F, De Buyzere ML, De Meyer T, et al. Arterial stiffness and influences of the metabolic syndrome: a cross-countries study. Atherosclerosis. 2014; 233(2):654 60. 12. Weng C, Yuan H, Yang K, Tang X, Huang Z, Huang L, Chen W, Chen F, Chen Z, Yang P. Gender-specific association between the metabolic syndrome and arterial stiffness in 8,300 subjects. Am J Med Sci. 2013;346(4):289 94. 13. Lehmann ED, Riley WA, Clarkson P, Gosling RG. Non-invasive assessment of cardiovascular disease in diabetes mellitus. Lancet. 1997;350 Suppl 1:SI14 9. 14. Zhou Y, Li Y, Xu L, Xu J, Wang A, Gao X, Wu S, Wei WB, Zhao X, Jonas JB. Asymptomatic polyvascular abnormalities in community (APAC) study in China: objectives, design and baseline characteristics. PLoS One. 2013;8(12):e84685. 15. Wang A, Liu X, Guo X, Dong Y, Wu Y, Huang Z, Xing A, Luo Y, Jonas JB, Wu S. Resting heart rate and risk of hypertension: results of the Kailuan cohort study. J Hypertens. 2014;32(8):1600 5. discussion 1605. 16. Wang A, Wu J, Zhou Y, Guo X, Luo Y, Wu S, Zhao X. Measures of adiposity and risk of stroke in China: a result from the Kailuan study. PLoS One. 2013; 8(4):e61665. 17. Wang A, Tao J, Guo X, Liu X, Luo Y, Huang Z, Chen S, Zhao X, Jonas JB, Wu S. The product of resting heart rate times blood pressure is associated with high brachial-ankle pulse wave velocity. PLoS One. 2014;9(9):e107852. 18. Kim YK. Impact of the metabolic syndrome and its components on pulse wave velocity. Korean J Intern Med. 2006;21(2):109 15. 19. Chen L, Zhu W, Mai L, Fang L, Ying K. The association of metabolic syndrome and its components with brachial-ankle pulse wave velocity in south China. Atherosclerosis. 2015;240(2):345 50. 20. Wang G, Zheng L, Li X, Wu J, Zhang L, Zhang J, Zou L, Zhang Y, Zhou Q, Fan H, et al. Using brachial-ankle pulse wave velocity to screen for metabolic syndrome in community populations. Sci Rep. 2015;5:9438. 21. Yamashina A, Tomiyama H, Arai T, Hirose K, Koji Y, Hirayama Y, Yamamoto Y, Hori S. Brachial-ankle pulse wave velocity as a marker of atherosclerotic vascular damage and cardiovascular risk. Hypertens Res. 2003;26(8):615 22. 22. Lin WY, Lai MM, Li CI, Lin CC, Li TC, Chen CC, Lin T, Liu CS. In addition to insulin resistance and obesity, brachial-ankle pulse wave velocity is strongly associated with metabolic syndrome in Chinese a population-based study (Taichung Community Health Study, TCHS). J Atheroscler Thromb. 2009; 16(2):105 12. 23. Kim YS, Kim DH, Choi BH, Sohn EH, Lee AY. Relationship between brachialankle pulse wave velocity and cognitive function in an elderly communitydwelling population with metabolic syndrome. Arch Gerontol Geriatr. 2009; 49(1):176 9. 24. Wu S, Lin H, Zhang C, Zhang Q, Zhang D, Zhang Y, Meng W, Zhu Z, Tang F, Xue F, et al. Association between erythrocyte parameters and metabolic syndrome in urban Han Chinese: a longitudinal cohort study. BMC Public Health. 2013;13:989. 25. Workalemahu T, Gelaye B, Berhane Y, Williams MA. Physical activity and metabolic syndrome among Ethiopian adults. Am J Hypertens. 2013;26(4):535 40. 26. Laurent S, Cockcroft J, Van Bortel L, Boutouyrie P, Giannattasio C, Hayoz D, Pannier B, Vlachopoulos C, Wilkinson I, Struijker-Boudier H. Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J. 2006;27(21):2588 605. 27. McEniery CM, Spratt M, Munnery M, Yarnell J, Lowe GD, Rumley A, Gallacher J, Ben-Shlomo Y, Cockcroft JR, Wilkinson IB. An analysis of prospective risk factors for aortic stiffness in men: 20-year follow-up from the Caerphilly prospective study. Hypertension. 2010;56(1):36 43.

Wang et al. BMC Cardiovascular Disorders (2016) 16:228 Page 10 of 10 28. Wang KL, Cheng HM, Sung SH, Chuang SY, Li CH, Spurgeon HA, Ting CT, Najjar SS, Lakatta EG, Yin FC, et al. Wave reflection and arterial stiffness in the prediction of 15-year all-cause and cardiovascular mortalities: a community-based study. Hypertension. 2010;55(3):799 805. 29. Vlachopoulos C, Aznaouridis K, Stefanadis C. Prediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysis. J Am Coll Cardiol. 2010;55(13):1318 27. 30. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith Jr SC, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/ National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735 52. Submit your next manuscript to BioMed Central and we will help you at every step: We accept pre-submission inquiries Our selector tool helps you to find the most relevant journal We provide round the clock customer support Convenient online submission Thorough peer review Inclusion in PubMed and all major indexing services Maximum visibility for your research Submit your manuscript at www.biomedcentral.com/submit